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Pour Picks

by io.github.bguillow-rgb
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pour_tonight_suggestion

Read-onlyIdempotent

A pour suggestion for right now, based on mood (e.g. 'unwinding', 'celebratory', 'contemplative'), occasion (e.g. 'nightcap', 'with friends', 'after dinner'), and season.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pour_tonight_suggestion"
  }
}

Input Schema

NameRequiredDescriptionDefault
moodNoHow you're feeling
seasonNoSeason to weight the pick toward — heavier, warming pours in winter; lighter in summer
occasionNoThe setting

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / mood / maxLength
      Added value: +120
    • addedInput schema / properties / occasion / maxLength
      Added value: +120
  2. First observed

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds only that the pick is situational/personalized; it does not say whether all inputs are optional with defaults, what is returned, or how the weighting behaves when inputs are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. The parenthetical examples are the only elaboration and they directly earn their place by illustrating the open-ended inputs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With zero required parameters and a fully documented schema, the description is nearly sufficient, and 'a pour suggestion' hints at the return. It stops short of explaining behavior when no inputs are supplied (which matters since all three are optional) or what form the suggestion takes, with no output schema to fall back on.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description goes beyond it by supplying concrete example values for the two open-ended string parameters ('unwinding', 'celebratory', 'contemplative'; 'nightcap', 'with friends', 'after dinner'), which the schema does not. Season semantics are already fully covered by the schema, so no extra credit there.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: produces a single pour suggestion for the current moment, keyed on mood, occasion, and season. This is clearly distinguishable from list/aggregate siblings like search_bottles or trending_bottles, though it never explicitly names how it differs from get_recommendations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"For right now" implies the usage context (an immediate, personal pick), and the three named inputs imply when it applies. However, there is no explicit when-to-use statement, no exclusions, and no routing to sibling tools like get_recommendations or find_similar.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Pour Picks toolsInspect
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